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Common Beans Imagery Dataset for Early Detection of Crop Diseases

Domaine:

agriculture

Type de record:

dataset
Créateur:
Laizer, HudsonMduma, NeemaMachuve, DinaLyimo, Tumaini
Éditeur:
Zenodo
Hôte:avatar

The annotated dataset consists of common beans leaf imagery for early diseases detection. The common beans crop leaves images were taken in Mbeya region in the Southern Highlands of Tanzania between 20th   October 2022 and 10th April 2023 using a mobile data collection tool, called the Open Data Kit (ODK). The crop leaf imagery dataset use case is developing machine learning models and end-user tools for early detection of (i) Bean anthracnose, and (ii) Bean rust diseases in common beans. The common leaf imagery data was collected from small holder farms using Samsung Galaxy A03 Core smartphones. 

All images are in the .zip files; “anthra.zip” has 13,531 images, “healthy.zip” has 24,973 images, and “rust.zip” has 20,568 images. A total of 59,072 image files are labelled.

This research project is financially supported by the International Development Research Centre (IDRC) and the Swedish International Development Cooperation Agency (SIDA) through the Artificial Intelligence for Agriculture and Food Systems Innovation Research Network (AI4AFS-IRN) administered by the African Technology Policy Studies Network (ATPS) with Grant Award Number: AI4AFS/GA/AFS-2504001568.

Visit

doi.org

Tasks

computer visionimage classification

Languages

Koma

Tags

Common beanBean anthracnoseBean rustLeaf imageryCrop diseases

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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